Getting Started with EegFun.jl

Installing Julia

EegFun.jl requires Julia 1.12.

The recommended way to install and manage Julia versions is with juliaup. Alternatively, download an installer directly from the Julia Downloads page.

The Julia REPL

Julia is an interactive language built around a Read-Eval-Print Loop (REPL). The REPL provides different modes accessed by special keys:

Key	Mode	Purpose
(default)	Julia mode	Execute Julia code
]	Package mode	Install and manage packages
?	Help mode	Access inline documentation
;	Shell mode	Run shell commands

Press Backspace to return to Julia mode from any other mode.

IDE Workflows

Most users pair the REPL with an editor that adds syntax highlighting and — most importantly — lets you send code directly into the live Julia REPL session. See IDE Workflows for a comparison of VS Code/VSCodium, Positron, JetBrains, and the Neovim + Iron.nvim terminal workflow.

Installing EegFun

You can install EegFun.jl through the standard Julia package manager.

Standard Installation

From the Julia REPL, enter Pkg mode by pressing ] and run:

add EegFun

Or using Pkg in the code:

using Pkg
Pkg.add("EegFun")

Note for plotting: EegFun.jl uses Makie.jl for visualizations. To display plots or use the interactive GUIs, you must also install a Makie backend of your choice:

• add GLMakie (Recommended for interactive GUIs and the Data Browser)

• add CairoMakie (Recommended for static, publication-quality plots or headless servers)

Development Version (vía GitHub)

To install the latest development version directly from GitHub:

using Pkg
Pkg.add(url="https://github.com/igmmgi/EegFun.jl")

Then load the package in any Julia REPL session:

using EegFun

First Steps

All EegFun functions are called with the EegFun. prefix. The fastest way to get started is to use our built-in tutorial datasets:

using EegFun
using GLMakie # Required for interactive plotting

# 1. Automatically download the tutorial datasets
data_dir = download_eegfun_datasets()
file_path = joinpath(data_dir, "participant1.bdf")

# 2. Load the raw recording
dat = EegFun.read_raw_data(file_path)

# 3. Attach an electrode layout
layout = EegFun.read_layout("biosemi72.csv")
EegFun.polar_to_cartesian_xy!(layout)
dat = EegFun.create_eegfun_data(dat, layout)

# 4. Browse the raw data interactively
EegFun.plot_databrowser(dat)

When you are ready to load your own data, simply replace `file_path` with the string path to your own file on disk (e.g., `EegFun.read_raw_data("C:/EEG/participant1.bdf")`).

Functions ending with `!` (e.g. `filter!`) mutate their input in-place. Functions without `!` return a new copy. Functions starting with `_` are internal helpers and not part of the public API.

EegFun Philosophy

EegFun.jl is designed with ease-of-use as a core principle, making it accessible even for those without extensive programming experience. However, whilst EegFun provides many interactive GUIs for data visualization and exploration, it is not a full GUI application — the package emphasises a code-based workflow that is intended to be simple and intuitive.

The package offers a mix of high-level and lower-level functions, including complete analysis pipelines that take you from raw data through to ERP analyses, while still allowing fine-grained control when needed. In practice, a complete EEG analysis can be accomplished with little to zero traditional "coding" — simply typing commands in the Julia REPL and/or combining them into small, readable/runnable scripts.

Supported Data Formats

Format	Extension(s)	Notes
BioSemi	.bdf	via BiosemiDataFormat.jl
BrainVision	.vhdr / .eeg / .vmrk	via BrainVisionDataFormat.jl
EEGLAB	.set / .fdt	basic support
FieldTrip	.mat	basic support

Additional file format support is planned for future releases. The format-specific packages are automatically installed as dependencies of EegFun.jl.

Next Steps and Resources

Resource	Link
EegFun.jl GitHub	github.com/igmmgi/EegFun.jl
Manual Preprocessing tutorial	Manual Preprocessing
All how-to guides	How-to Guides
Julia learning resources	julialang.org/learning
Julia cheat sheet	cheatsheet.juliadocs.org
MATLAB–Python–Julia cheat sheet	cheatsheets.quantecon.org
Makie.jl (plotting)	docs.makie.org
DataFrames.jl	dataframes.juliadata.org